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The integration of sensor technology and automated analytics in wearable devices marks a significant advancement in sports science, aiming to proactively prevent injuries and optimize athletic performance. This paper delves into the application of advanced sensor systems and automated data analysis tools in the realm of athletics. These wearables, equipped with a multitude of sensors, continuously monitor an athlete's physiological and biomechanical data, including heart rate, muscle activity, and movement dynamics. The automated processing of this data through machine learning algorithms enables real-time insights and predictive analytics, offering a novel approach to injury prevention. By analyzing the intricate patterns of an athlete's performance metrics, these sensor-augmented wearables facilitate a data-driven strategy for reducing risks of soft-tissue and heat-related injuries. This technology empowers coaches and athletes with actionable insights, fostering a safer and more efficient training environment. Our exploration showcases the transformative impact of sensor-enhanced wearables and automated analytics in elevating the standards of injury prevention and performance optimization in sports.
Kovoor et al. (2024) studied this question.